INTERVIEW: Nicole Lim – From Prompts to Results: How ChatGPT Helped Transform Enrollment Strategy

Growing program enrollment to meet the demands of a business can be daunting, and yet evaluating the process systematically can unlock unexpected growth opportunities. That’s exactly what happened when Nicole Lim, Portfolio Coordinator at UCLA Extension’s Engineering Department, turned to prompt engineering with ChatGPT to help her team rethink how they communicated program value—ensuring their messaging resonated with the real goals and motivations of engineering professionals. Focusing on two of UCLA Extension’s flagship programs—Analog Circuit Design and Technical Management—she used ChatGPT prompting to uncover insights that deepened engagement and supported more students in staying on track through graduation. This was a deliberate and strategic use of technology, aimed at aligning each program more closely with the career ambitions and real-world needs of engineering and technical professionals.

This pilot project was selected as part of the UCLA Call for OpenAI Project Proposals and received ChatGPT Enterprise licenses, along with in-kind support from the AI Innovation Initiative led by UCLA Digital & Technology Solutions.

Early Outcomes from UCLA’s ChatGPT Adoption

As UCLA became the first university in California to adopt ChatGPT Enterprise, Lim’s project stood out as one of its earliest applications—demonstrating how generative AI could serve not just as a tool, but as a catalyst for enhancing program engagement, refining value propositions, and improving student outcomes.

Rather than relying on conventional outreach methods, she led a cross-functional effort grounded in a systematic evaluation process: using artificial intelligence. Using prompts and interacting with ChatGPT through collaborative testing, iteration, and integration, the team surfaced insights, validated them, and then reshaped how the program connected with prospective students.

This wasn’t just a data-driven decision and a simple query. It was based on a process of prompting ChatGPT, interpreting its responses, and testing those ideas collaboratively across a cross-functional team and based on prior experiences and data. And over time, it led to a breakthrough concept and resulted in equally astounding results. By taking a more thoughtful, student-centered approach, Nicole Lim and her team raised the graduation rate of the Analog Circuit Design Program from 80% to 96%. At the same time, they saw earlier enrollments and deeper, long-term partnerships form through the Technical Management Program.

The impact was clear. Many students committed to the full six-course sequence and completed the Analog Circuit Design Program, while satisfied learners in the Technical Management Program referred colleagues into future cohorts. For many, program completion became a launching point for continued learning—creating a ripple effect that deepened trust in the institution and showcased the power of a well-aligned, student-driven experience.

But it wasn’t the result that mattered most, it was how they got there—and the fact that the project has changed the way the team uses AI to support their work.

Starting with ChatGPT and Prompting the Right Questions

Lim’s first step was exploring how ChatGPT could help them think differently about marketing and outreach. Rather than plugging in a prompt and taking the first answer, she and her team approached the tool like a thought partner.

I asked it really important questions like, How should we strategize and refine our value proposition and support business development? What is the source of this information, what formula generated this prompt?

But the insights didn’t come from AI alone — they came from what the team chose to do with it. Each team member generated prompts independently and brought the results to group discussions. “We would all go write prompts in ChatGPT, show the outcome and analysis, and then we discuss those outcomes within our team and select which ones to adopt,” Lim explained. This iterative back-and-forth became the foundation of their planning — a continuous feedback loop between AI suggestions and human judgment.

ChatGPT-supported Personalized Webinars Over Generic Outreach

One of the first major insights that surfaced through this process was the realization that a different program outreach plan, supported by ChatGPT prompting and tools, was a necessity since general information sessions weren’t cutting it. The team had been relying on broad webinars, even though many of their prospective students came from specific companies with their own specific perspectives and needs.

Based on the wisdom from the Program Director and engineering instructor’s decision to refocus on increasing business development efforts for the newly launched Systems Engineering Program, following a human-led strategic planning process for business development, the team incorporated ChatGPT during the execution and monitoring phases to support real-time messaging refinement and learner engagement analysis. Thus, enrollment projections more than doubled, exceeding initial forecast, which opened the door to using ChatGPT to support and retain this increased volume of student engagement in this gateway course. Lim bridged the gap between executive vision and day-to-day execution by translating strategic goals into clear project workflows, timelines, and team processes—ensuring that high-level plans became actionable and measurable outcomes at a larger scale.

The personalized format helped streamline the decision-making process for participants, eliminating confusion and creating a more relevant, trusted connection.

Building a Collaborative and Ethical Culture Around AI

Throughout the project, collaboration remained central. Lim relied on visual workboards to organize priorities and invited the team to choose which tasks matched their strengths. She also credits the BruinTech community with helping her design the project framework and set a clear timeline for execution.

Responsible AI use was a constant priority. “The main priority is AI literacy,” Lim noted. “Knowing that there could be some errors in the outputs, or knowing that there could be some bias in it that could affect the outcome.” Her team avoided using any student data and referred to companies only in broad terms, ensuring privacy was protected.

The process of AI adoption wasn’t immediate either. For example, Lim shared that her supervisor was initially unsure how ChatGPT could help—until it saved her hours on a repetitive task.

She didn’t see how it could help her workload, until she used it for organizing data in an Excel sheet… Instead of spending two hours on it, she just spent 15 minutes fixing it.

Better Questions, Better Outcomes

Lim emphasized that AI didn’t hand them a roadmap — it simply helped them reflect more deeply on their approach.

ChatGPT didn’t give us the final answer…It just helped us ask better questions.

Her story demonstrates that success isn’t found in the tool alone, but in how a team uses it: thoughtfully, collaboratively, and with a clear commitment to improving the experience for every learner involved.